By: Sorab Ghaswalla
In a previous newsletter I had talked of how machine learning (ML), a sub-discipline of artificial intelligence (AI) was “creating” and editing content. In the last few years, AI has “invaded” almost every profession. AI has replaced humans in some tasks, and is heading toward replacing some more.
One area where ML has been deployed with a degree of success is content, specifically, content that is based on data, i.e. content that is more “black and white” minus shades of gray.
News outfits, for example Bloomberg, have successfully deployed AI in the filing of a certain type of business report - company results, or markets’ reports. Others are using this tech to make machines file sports reports, even.
AI can “create” fresh content and even edit the already created ones. There are also some state-of-the-art paraphrasing tools available that come handy for re-writes. Grammer-check software, even. More so, a slice of modern-day “digital” marketing activities has also been taken over by AI.
Suffice to say any process that has some kind of repetitive task is well-served by ML as the latter is used to automate processes running on copious amounts of data that humans simply cannot cope with.
So popular has the use of AI in content generation become that online universities are actually offering courses where students are taught how to use AI tools in the creation of content, and in digital marketing. The target audience of such courses are content marketers whose primary weapon is content forms such as blogs, videos, white papers, and so on.
Would it be correct then to say that ML has gone mainstream in the production of content? The answer is no.
On a scale of 1 - 10, ML is probably at 1.5 in the world of content. Quality is still an issue where machine generated or even machine corrected content is concerned. While AI-driven editing and para-phrasing tech has certainly improved, things are far from being perfect.
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